Katharina Dost

According to our database, Katharina Dost authored at least 15 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Forecasting severe respiratory disease hospitalizations using machine learning algorithms.

Steffen Albrecht, David Broderick, Katharina Dost, Isabella Cheung, Nhung Nghiem, Milton Wu, Johnny Zhu, Nooriyan Poonawala-Lohani, Sarah Jamison, Damayanthi Rasanathan, Sue Huang, Adrian Trenholme, Alicia Stanley, Shirley Lawrence, Samantha Marsh, Lorraine Castelino, Janine Paynter, Nikki Turner, Peter McIntyre, Patricia Riddle, Cameron Grant, Gillian Dobbie, Jörg Simon Wicker

BMC Medical Informatics Decis. Mak., December, 2024

AdductHunter: identifying protein-metal complex adducts in mass spectra.

Derek Long, Liam Eade, Matthew P. Sullivan, Katharina Dost, Samuel M. Meier-Menches, David C. Goldstone, Christian G. Hartinger, Jörg S. Wicker, Katerina Taskova

J. Cheminformatics, December, 2024

Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath.

Jasmin Hafner, Tim Lorsbach, Sebastian Schmidt, Liam Brydon, Katharina Dost, Kunyang Zhang, Kathrin Fenner, Jörg Wicker

J. Cheminformatics, December, 2024

Regional bias in monolingual English language models.

Jiachen Lyu, Katharina Dost, Yun Sing Koh, Jörg Wicker

Mach. Learn., September, 2024

Hitting the target: stopping active learning at the cost-based optimum.

Zac Pullar-Strecker, Katharina Dost, Eibe Frank, Jörg Wicker

Mach. Learn., April, 2024

2023

Combatting over-specialization bias in growing chemical databases.

Katharina Dost, Zac Pullar-Strecker, Liam Brydon, Kunyang Zhang, Jasmin Hafner, Patricia J. Riddle, Jörg S. Wicker

J. Cheminformatics, December, 2023

Poison is Not Traceless: Fully-Agnostic Detection of Poisoning Attacks.

Xinglong Chang, Katharina Dost, Gillian Dobbie, Jörg Wicker

CoRR, 2023

Memento: Facilitating Effortless, Efficient, and Reliable ML Experiments.

Zac Pullar-Strecker, Xinglong Chang, Liam Brydon, Ioannis Ziogas, Katharina Dost, Jörg Wicker

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Interpretability Meets Generalizability: A Hybrid Machine Learning System to Identify Nonlinear Granger Causality in Global Stock Indices.

Yixiao Lu, Yokiu Lee, Haoran Feng, Johnathan Leung, Alvin Cheung, Katharina Dost, Katerina Taskova, Thomas Lacombe

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Targeted Attacks on Time Series Forecasting.

Zeyu Chen, Katharina Dost, Xuan Zhu, Xinglong Chang, Gillian Dobbie, Jörg Wicker

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability.

Xinglong Chang, Katharina Dost, Kaiqi Zhao, Ambra Demontis, Fabio Roli, Gillian Dobbie, Jörg Wicker

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

2022

Divide and Imitate: Multi-cluster Identification and Mitigation of Selection Bias.

Katharina Dost, Hamish Duncanson, Ioannis Ziogas, Patricia Riddle, Jörg Wicker

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

2021

Intriguing Usage of Applicability Domain: Lessons from Cheminformatics Applied to Adversarial Learning.

Luke Chang, Katharina Dost, Kaiqi Zhao, Ambra Demontis, Fabio Roli, Gill Dobbie, Jörg Wicker

CoRR, 2021

2020

The Semantic Spreadsheet.

Behzad Farokhi, Katharina Dost, Gerald Weber, Jing Sun, Christof Lutteroth

Proceedings of the 25th International Conference on Engineering of Complex Computer Systems, 2020

Your Best Guess When You Know Nothing: Identification and Mitigation of Selection Bias.

Katharina Dost, Katerina Taskova, Patricia Riddle, Jörg Wicker

Proceedings of the 20th IEEE International Conference on Data Mining, 2020